The invention belongs to the field of disordered sorting machine vision, and particularly relates to a method for improving the recognition and positioning precision of automobile sheet metal workpieces. The method comprises the following steps of: 1, acquiring a complete scene image of a workpiece to be captured, carrying out preprocessing, completing instance segmentation on the workpiece in the image, and extracting the edge of a two-dimensional image according to an instance segmentation result; 2, preprocessing the acquired point cloud data of the to-be-captured workpiece scene, and further extracting the edge of the point cloud data by taking the edge of the extracted two-dimensional image as an index; calculating point pair features in the edge of the point cloud, and establishing global model description; and 3, carrying out online model matching, obtaining candidate poses by adopting a voting method based on a Hough voting principle, clustering the candidate poses by adopting a connectivity density clustering algorithm, and optimizing the poses by adopting an ICP registration algorithm. According to the invention, the recognition and positioning precision of the automobile sheet metal part can be greatly improved while the workpiece recognition speed is ensured.